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Legitimacy and Public Policy: Seeing Beyond Effectiveness, Efficiency, and Performance

2008· article· en· W2124056250 on OpenAlexaffabout
Jennifer Wallner

Bibliographic record

VenuePolicy Studies Journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLegitimacyPublic administrationStakeholderPublic policyPolitical sciencePublic relationsArgument (complex analysis)LegislatureRealmGovernment (linguistics)Policy studiesPoliticsLaw

Abstract

fetched live from OpenAlex

Studies of failure typically assess public policies through the lenses of effectiveness, efficiency, and performance. Here I wish to propose a further dimension to the evaluation and assessment of policy failure—legitimacy. The substantive elements of public policies and the procedural steps taken by authoritative decision makers during the policy cycle affect the perception of policy legitimacy held by both stakeholders and the public. In substantive terms, policy content should align with the dominant attitudes of the affected policy community and, ideally, the broader public. Procedurally, factors such as policy incubation, the emotive appeals deployed to gain support for an initiative, and the processes of stakeholder engagement shape the legitimacy of public policies and the governments who promote them. This argument is based on a comparison of education reform in two Canadian provinces during the 1990s. Governments in Alberta and Ontario pursued common agendas of education reform, but while Alberta achieved success, the Ontario government experienced a series of setbacks and lost the support of education stakeholders and the public. The root of Ontario's failures lies in the realm of legitimacy. These findings highlight the fact that the strategies used for enacting policy change may fail to bring about the necessary consensus among societal actors to sustain a new policy direction and calls attention to our need to better understand how governments can achieve meaningful public participation while still achieving legislative success in an efficient fashion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.115
metaresearch head score (Gemma)0.190
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1150.190
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0130.008
Science and technology studies0.0090.125
Scholarly communication0.0390.049
Open science0.0030.019
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.370
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations207
Published2008
Admission routes2
Has abstractyes

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Same venuePolicy Studies JournalSame topicPolicy Transfer and LearningFrench-language works237,207